The invention relates generally to the field of patterned arrays. More particularly, the invention relates to novel arrangements of layouts that improve the location and identification of specific sites on the arrays.
Arrays provide a number of individual sites at permanently or transiently fixed locations on a surface. Particularly useful arrays have sites that contain chemical groups or biological molecules, which can be identical or different among the many sites, and can interact with other materials of interest, such as a biological sample. Sites can be located by taking an image of the substrate surface, such as by a planar image or by line scanning. The image data is processed to locate and identify at least a portion of the sites. Where a chemical or biological interaction occurs at a particular site, the interaction can also be detected at the site and correlated with the location and identity of the site, as well as the particular group or molecule present at the site.
Sites are frequently arranged in a regular geometrical pattern, such as a checkerboard or hexagonal grid, to maximize the number of sites available on the substrate surface and to facilitate the location of sites by automated instruments. The location of individual sites on a surface can be identified by various registration methods. Conventional registration (sometimes referred to as “full registration”) is based on starting from predetermined locations within the array and advancing through the sites one at a time by expected location. An example of a full registration algorithm uses one or more reliable reference location (“fiducial”) such as an edge or other identifiable landmark. The sites in a regular pattern can then be identified using the fiducials for absolute reference, proceeding through the rows (or columns) based on knowledge a priori of the geometrical pattern, site size and pitch (spacing), collectively a “reference pattern”. Full registration for every site on a substrate can be mechanically and computationally burdensome, however, due to the difficulty of accurately measuring absolute distances from a few reference points that are relatively distant.
To supplement full registration methods, local registration can be performed rapidly using a simple two-dimensional cross-correlation between the signals in detected site locations and the reference pattern. The alternate approach might be termed “rigid registration”. While the method can be based in part on the ability to detect fiducials, the rigid approach takes advantage of knowledge a priori of the pattern (such as hexagonal), so that the location an individual site can be fine-tuned locally by observing its position relative to its neighbors. For example, a least squares fit can be performed with the detected signal against a rigid grid of coordinates (such as a kernel hexagonal array) serving as the reference pattern. The fit is completed via an affine transformation to account for large scale distortions that can be present throughout the image. In some registration methods, the local registration is sufficiently robust to obviate the necessity for measuring each location absolutely with respect to the fiducials, so that full registration is performed only at predetermined intervals, reducing the overall burden of the registration method. The locations can be registered simultaneously rather than one at a time, with a reduced sensitivity to large-scale distortions.
Nevertheless, the fitting routine is computationally expensive for large area arrays with a large number (high density) of objects. An additional challenge with the approach is that it is not sensitive to local, small scale distortions; such distortions can similarly induce miscorrelation between the detected array and the kernel. Thus, the rigid registration algorithm may not be ideally suited to large area microarrays.
Unfortunately, cross-correlation checks are not always sensitive to integral offsets (such as vertical or horizontal translation) or “walk-offs”, where the registration can appear correct locally within a geometrical pattern of sites, but each site is mistaken for its neighbor. Reliance on local registration can also break down if attempted from within the repeating expanse of a regular pattern, without the absolute reference of a fiducial. Although some walk-off errors can be corrected when a fiducial is subsequently found, walk-offs can accumulate so that the compounded error can be difficult to resolve unambiguously. Where the correct identification of a site is significant, such as with random bead arrays, the correlation of an interaction with the wrong site location can result in an erroneous interpretation. Thus, there is a need for an arrangement of sites that is resistant to walk-off errors.